Sergio Lucia
Research Subjects
Sergio Lucia has a total of 3 co-authors. Here are the top co-authors by number of shared publications:
- Florian Messerer
Department of Microsystems Engineering, University of Freiburg, Freiburg, Germany
1 shared publication - Moritz Diehl
Department of Microsystems Engineering (IMTEK) and Department of Mathematics, University of Freiburg, Freiburg, Germany
1 shared publication - Moritz Heinlein1 shared publication
Latest Publications
- Open Access
Ellipsoidal partitions for improved multi-stage robust model predictive control
Ellipsoidal tube-based model predictive control methods effectively account for the propagation of the reachable set, typically employing linear feedback policies. In contrast, scenario-based approaches offer more flexibility in the feedback structure by considering different control actions for different branches of a scenario tree. However, they face challenges in ensuring rigorous guarantees. This work aims to integrate the strengths of both methodologies by enhancing ellipsoidal tube-based MPC with a scenario tree formulation. The uncertainty ellipsoids are partitioned by halfspaces such that each partitioned set can be controlled independently. The proposed ellipsoidal multi-stage approach is demonstrated in a human-robot system, highlighting its advantages in handling uncertainty while maintaining computational tractability.
Open AccessEllipsoidal partitions for improved multi-stage robust model predictive control
Ellipsoidal tube-based model predictive control methods effectively account for the propagation of the reachable set, typically employing linear feedback policies. In contrast, scenario-based approaches offer more flexibility in the feedback structure by considering different control actions for different branches of a scenario tree. However, they face challenges in ensuring rigorous guarantees. This work aims to integrate the strengths of both methodologies by enhancing ellipsoidal tube-based MPC with a scenario tree formulation. The uncertainty ellipsoids are partitioned by halfspaces such that each partitioned set can be controlled independently. The proposed ellipsoidal multi-stage approach is demonstrated in a human-robot system, highlighting its advantages in handling uncertainty while maintaining computational tractability.